《Redis GeoHash：实现附近的人功能（附代码）》（672）

# 🌍 Redis GeoHash：轻松实现「附近的人」功能（附代码） 

在社交、外卖、打车等应用中，「附近的人」功能十分常见。Redis 的 **GeoHash** 正是为此而生！它通过将经纬度编码为字符串，高效存储和查询地理位置数据。 

## 🔍 GeoHash 原理 
GeoHash 将二维经纬度映射为一维字符串，前缀相同的点在地理上相近。例如： 
- 北京天安门：`wx4g0b8` 
- 附近地点：`wx4g0b9`（前缀相同） 

## 🚀 Redis 实现步骤 

### 1️⃣ 添加地理位置 
```python
import redis

r = redis.Redis()
# 添加用户位置（经度、纬度、名称）
r.geoadd("users:location", 116.404, 39.915, "user1") 
r.geoadd("users:location", 116.405, 39.916, "user2")
```

### 2️⃣ 查询附近的人 
```python
# 查询 user1 附近 1km 内的用户
results = r.georadiusbymember(
  "users:location",
  "user1",
  1, # 半径 1km
  unit="km",
  withdist=True # 返回距离
)
print(results) # [('user2', 0.12), ...]
```

### 3️⃣ 获取距离 
```python
distance = r.geodist("users:location", "user1", "user2", unit="km")
print(f"相距 {distance} km") # 相距 0.12 km
```

## 💡 优势 
- ⚡ **高性能**：基于 Redis 内存操作，查询速度极快 
- 📍 **精准排序**：支持按距离筛选和排序 
- 🔧 **简单 API**：几行代码即可实现功能 

## 🎯 应用场景 
- 社交 App 的「附近好友」 
- 外卖/快递的「附近骑手」 
- 共享单车的「最近车辆」 

用 Redis GeoHash，轻松让你的应用「定位」更精准！📍 

（代码示例基于 Python + Redis，其他语言类似）
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